Neural systems engineering

被引:87
作者
Furber, Steve [1 ]
Temple, Steve [1 ]
机构
[1] Univ Manchester, Sch Comp Sci, Manchester M13 9PL, Lancs, England
基金
英国工程与自然科学研究理事会;
关键词
neural networks; computer engineering; computational neuroscience; massively parallel computing; spiking neurons;
D O I
10.1098/rsif.2006.0177
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
The quest to build an electronic computer based on the operational principles of biological brains has attracted attention over many years. The hope is that, by emulating the brain, it will be possible to capture some of its capabilities and thereby bridge the very large gulf that separates mankind from machines. At present, however, knowledge about the operational principles of the brain is far from complete, so attempts at emulation must employ a great deal of assumption and guesswork to fill the gaps in the experimental evidence. The sheer scale and complexity of the human brain still defies attempts to model it in its entirety at the neuronal level, but Moore's Law is closing this gap and machines with the potential to emulate the brain (so far as we can estimate the computing power required) are no more than a decade or so away. Do computer engineers have something to contribute, alongside neuroscientists, psychologists, mathematicians and others, to the understanding of brain and mind, which remains as one of the great frontiers of science?
引用
收藏
页码:193 / 206
页数:14
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